feat: add SuperComponent

examples/example_files/sample.md

@@ -0,0 +1,65 @@
+---
+type: intro
+date: 1.1.2023
+---
+```bash
+pip install farm-haystack
+```
+## What to build with Haystack
+
+- **Ask questions in natural language** and find granular answers in your own documents.
+- Perform **semantic search** and retrieve documents according to meaning not keywords
+- Use **off-the-shelf models** or **fine-tune** them to your own domain.
+- Use **user feedback** to evaluate, benchmark and continuously improve your live models.
+- Leverage existing **knowledge bases** and better handle the long tail of queries that **chatbots** receive.
+- **Automate processes** by automatically applying a list of questions to new documents and using the extracted answers.
+
+![Logo](https://raw.githubusercontent.com/deepset-ai/haystack/main/docs/img/logo.png)
+
+
+## Core Features
+
+-   **Latest models**: Utilize all latest transformer based models (e.g. BERT, RoBERTa, MiniLM) for extractive QA, generative QA and document retrieval.
+-   **Modular**: Multiple choices to fit your tech stack and use case. Pick your favorite database, file converter or modeling framework.
+-   **Open**: 100% compatible with HuggingFace's model hub. Tight interfaces to other frameworks (e.g. Transformers, FARM, sentence-transformers)
+-   **Scalable**: Scale to millions of docs via retrievers, production-ready backends like Elasticsearch / FAISS and a fastAPI REST API
+-   **End-to-End**: All tooling in one place: file conversion, cleaning, splitting, training, eval, inference, labeling ...
+-   **Developer friendly**: Easy to debug, extend and modify.
+-   **Customizable**: Fine-tune models to your own domain or implement your custom DocumentStore.
+-   **Continuous Learning**: Collect new training data via user feedback in production & improve your models continuously
+
+|  |  |
+|-|-|
+| :ledger: [Docs](https://haystack.deepset.ai/overview/intro) | Usage, Guides, API documentation ...|
+| :beginner: [Quick Demo](https://github.com/deepset-ai/haystack/#quick-demo) | Quickly see what Haystack offers |
+| :floppy_disk: [Installation](https://github.com/deepset-ai/haystack/#installation) | How to install Haystack |
+| :art: [Key Components](https://github.com/deepset-ai/haystack/#key-components) | Overview of core concepts |
+| :mortar_board: [Tutorials](https://github.com/deepset-ai/haystack/#tutorials) | Jupyter/Colab Notebooks & Scripts |
+| :eyes: [How to use Haystack](https://github.com/deepset-ai/haystack/#how-to-use-haystack) | Basic explanation of concepts, options and usage |
+| :heart: [Contributing](https://github.com/deepset-ai/haystack/#heart-contributing) | We welcome all contributions! |
+| :bar_chart: [Benchmarks](https://haystack.deepset.ai/benchmarks/v0.9.0) | Speed & Accuracy of Retriever, Readers and DocumentStores |
+| :telescope: [Roadmap](https://haystack.deepset.ai/overview/roadmap) | Public roadmap of Haystack |
+| :pray: [Slack](https://haystack.deepset.ai/community/join) | Join our community on Slack |
+| :bird: [Twitter](https://twitter.com/deepset_ai) | Follow us on Twitter for news and updates |
+| :newspaper: [Blog](https://medium.com/deepset-ai) | Read our articles on Medium |
+
+
+## Quick Demo
+
+The quickest way to see what Haystack offers is to start a [Docker Compose](https://docs.docker.com/compose/) demo application:
+
+**1. Update/install Docker and Docker Compose, then launch Docker**
+
+```
+    # apt-get update && apt-get install docker && apt-get install docker-compose
+    # service docker start
+```
+
+**2. Clone Haystack repository**
+
+```
+    # git clone https://github.com/deepset-ai/haystack.git
+```
+
+### 2nd level headline for testing purposes
+#### 3rd level headline for testing purposes

examples/example_files/sample_1.csv

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+Name,Age
+John Doe,27
+Jane Smith,37
+Mike Johnson,47